2,748 patient records provide a large-scale collection of unstructured ultrasound clinical reports. The dataset captures real-world variability in radiology reporting styles, anatomical descriptions, and diagnostic terminology. It was authored by InfoBayAI and last updated on June 4, 2026.
Use Cases
- Train diagnostic AI models based on unstructured textual findings.
- Develop clinical NLP systems based on radiology reporting styles.
- Analyze anatomical descriptions and diagnostic terminology variability.
Strengths
- Contains data from 2,748 patients.
- Captures real-world variability in radiology reporting styles.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
Provenance
- Source
- InfoBayAI
- Freshness
- Last updated 2026-06-04 06:17:55.